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DBMS > ArangoDB vs. Google Cloud Datastore vs. Titan

System Properties Comparison ArangoDB vs. Google Cloud Datastore vs. Titan

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Editorial information provided by DB-Engines
NameArangoDB  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonTitan  Xexclude from comparison
Titan has been decommisioned after the takeover by Datastax. It will be removed from the DB-Engines ranking. A fork has been open-sourced as JanusGraph.
DescriptionNative multi-model DBMS for graph, document, key/value and search. All in one engine and accessible with one query language.Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformTitan is a Graph DBMS optimized for distributed clusters.
Primary database modelDocument store
Graph DBMS
Key-value store
Search engine
Document storeGraph DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.77
Rank#87  Overall
#15  Document stores
#5  Graph DBMS
#12  Key-value stores
#10  Search engines
Score4.49
Rank#79  Overall
#12  Document stores
Websitearangodb.comcloud.google.com/­datastoregithub.com/­thinkaurelius/­titan
Technical documentationdocs.arangodb.comcloud.google.com/­datastore/­docsgithub.com/­thinkaurelius/­titan/­wiki
Social network pagesLinkedInTwitterFacebookYouTubeInstagram
DeveloperArangoDB Inc.GoogleAurelius, owned by DataStax
Initial release201220082012
Current release3.11.5, November 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2; Commercial license (Enterprise) availablecommercialOpen Source infoApache license, version 2.0
Cloud-based only infoOnly available as a cloud servicenoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
ArangoDB Cloud –The Managed Cloud Service of ArangoDB. Provides fully managed, and monitored cluster deployments of any size, with enterprise-grade security. Get started for free and continue for as little as $0,21/hour.
Implementation languageC++Java
Server operating systemsLinux
OS X
Windows
hostedLinux
OS X
Unix
Windows
Data schemeschema-free infoautomatically recognizes schema within a collectionschema-freeyes
Typing infopredefined data types such as float or dateyes infostring, double, boolean, list, hashyes, details hereyes
XML support infoSome form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.no
Secondary indexesyesyesyes
SQL infoSupport of SQLnoSQL-like query language (GQL)no
APIs and other access methodsAQL
Foxx Framework
Graph API (Gremlin)
GraphQL query language
HTTP API
Java & SpringData
JSON style queries
VelocyPack/VelocyStream
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster
Supported programming languagesC#
C++
Clojure
Elixir
Go
Java
JavaScript (Node.js)
PHP
Python
R
Rust
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Clojure
Java
Python
Server-side scripts infoStored proceduresJavaScriptusing Google App Engineyes
TriggersnoCallbacks using the Google Apps Engineyes
Partitioning methods infoMethods for storing different data on different nodesSharding infosince version 2.0Shardingyes infovia pluggable storage backends
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replication with configurable replication factorMulti-source replication using Paxosyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infocan be done with stored procedures in JavaScriptyes infousing Google Cloud Dataflowyes infovia Faunus, a graph analytics engine
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency infoconfigurable per collection or per write
Immediate Consistency
OneShard (highly available, fault-tolerant deployment mode with ACID semantics)
Immediate Consistency or Eventual Consistency depending on type of query and configuration infoStrong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.Eventual Consistency
Immediate Consistency
Foreign keys infoReferential integrityyes inforelationships in graphsyes infovia ReferenceProperties or Ancestor pathsyes infoRelationships in graph
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes infoSupports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcast
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.no
User concepts infoAccess controlyesAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)User authentification and security via Rexster Graph Server
More information provided by the system vendor
ArangoDBGoogle Cloud DatastoreTitan
Specific characteristicsGraph and Beyond. With more than 11,000 stargazers on GitHub, ArangoDB is the leading...
» more
Competitive advantagesConsolidation: As a native multi-model database, can be used as a full blown document...
» more
Typical application scenariosNative multi-model in ArangoDB is being used for a broad range of projects across...
» more
Key customersCisco, Barclays, Refinitive, Siemens Mentor, Kabbage, Liaison, Douglas, MakeMyTrip,...
» more
Market metricsArangoDB is the leading native multi-model database with over 11,000 stargazers on...
» more
Licensing and pricing modelsVery permissive Apache 2 License for Community Edition & commercial licenses are...
» more

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More resources
ArangoDBGoogle Cloud DatastoreTitan
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Amazon DynamoDB Storage Backend for Titan: Distributed Graph Database | Amazon Web Services
24 August 2015, AWS Blog

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Titan Graph Database Integration with DynamoDB: World-class Performance, Availability, and Scale for New Workloads
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